CMU talk: Techniques for Learning 3D Maps

Title: Techniques for Learning 3D Maps

Dr. Wolfram Burgard
Dept. of Computer Science
University of Freiburg

Monday, November 17th

Abstract: Learning maps is a fundamental aspect in mobile robotics, as maps support various tasks including path planning and localization. Whereas the problem of learning maps has been extensively studied for indoor settings, novel field robotics projects have substantially increased the interest in effective representations of outdoor environments. In this talk, we will present our recent results in learning highly accurate multi-level surface maps, which are an extension of elevation maps towards multiple levels. We will describe how multi-level surface maps can be utilized for motion planning and localization. We present an application, in which Junior, the DARPA Grand Challenge entry robot of Stanford University, autonomously drives through a large parking garage and carries out an autonomous parking maneuver. Finally, we will briefly describe our approaches to learning surface maps using variants of Gaussian Processes.

Speaker Bio: Wolfram Burgard is an associate professor for computer science at the University of Freiburg where he heads of the Laboratory for Autonomous Intelligent Systems. He received his Ph.D.~degree in Computer Science from the University of Bonn in 1991. His areas of interest lie in artificial intelligence and mobile robots. Over the past years his research mainly focused on the development of robust and adaptive techniques for state estimation and control of autonomous mobile robots. He and his group developed several innovative probabilistic techniques for robot navigation and control. They cover different aspects such as localization, map-building, path-planning, and exploration.